Key Visual Features for Rapid Categorization of Animals in Natural Scenes

In speeded categorization tasks, decisions could be based on diagnostic target features or they may need the activation of complete representations of the object. Depending on task requirements, the priming of feature detectors through top–down expectation might lower the threshold of selective units or speed up the rate of information accumulation. In the present paper, 40 subjects performed a rapid go/no-go animal/non-animal categorization task with 400 briefly flashed natural scenes to study how performance depends on physical scene characteristics, target configuration, and the presence or absence of diagnostic animal features. Performance was evaluated both in terms of accuracy and speed and d′ curves were plotted as a function of reaction time (RT). Such d′ curves give an estimation of the processing dynamics for studied features and characteristics over the entire subject population. Global image characteristics such as color and brightness do not critically influence categorization speed, although they slightly influence accuracy. Global critical factors include the presence of a canonical animal posture and animal/background size ratio suggesting the role of coarse global form. Performance was best for both accuracy and speed, when the animal was in a typical posture and when it occupied about 20–30% of the image. The presence of diagnostic animal features was another critical factor. Performance was significantly impaired both in accuracy (drop 3.3–7.5%) and speed (median RT increase 7–16 ms) when diagnostic animal parts (eyes, mouth, and limbs) were missing. Such animal features were shown to influence performance very early when only 15–25% of the response had been produced. In agreement with other experimental and modeling studies, our results support fast diagnostic recognition of animals based on key intermediate features and priming based on the subject's expertise

LIA@CLEF 2018: Mining events opinion argumentation from raw unlabeled Twitter data using convolutional neural network

International audienceSocial networks on the Internet are becoming increasingly important in our society. In recent years, this type of media, through communication platforms such as Twitter, has brought new research issues due to the massive size of data exchanged and the important number of ever-increasing users. In this context, the CLEF 2018 Mining opinion argumentation task aims to retrieve, for a specific event (festival name or topic), the most diverse argumentative microblogs from a large collection of tweets about festivals in different languages. In this paper, we propose a four-step approach for extracting argumentative microblogs related to a specific query (or event) while no reference data is provided

Observing Exoplanets with High-Dispersion Coronagraphy. II. Demonstration of an Active Single-Mode Fiber Injection Unit

High-dispersion coronagraphy (HDC) optimally combines high contrast imaging techniques such as adaptive optics/wavefront control plus coronagraphy to high spectral resolution spectroscopy. HDC is a critical pathway towards fully characterizing exoplanet atmospheres across a broad range of masses from giant gaseous planets down to Earth-like planets. In addition to determining the molecular composition of exoplanet atmospheres, HDC also enables Doppler mapping of atmosphere inhomogeneities (temperature, clouds, wind), as well as precise measurements of exoplanet rotational velocities. Here, we demonstrate an innovative concept for injecting the directly-imaged planet light into a single-mode fiber, linking a high-contrast adaptively-corrected coronagraph to a high-resolution spectrograph (diffraction-limited or not). Our laboratory demonstration includes three key milestones: close-to-theoretical injection efficiency, accurate pointing and tracking, on-fiber coherent modulation and speckle nulling of spurious starlight signal coupling into the fiber. Using the extreme modal selectivity of single-mode fibers, we also demonstrated speckle suppression gains that outperform conventional image-based speckle nulling by at least two orders of magnitude.Comment: 10 pages, 7 figures, accepted by Ap

Tubular space truss structure for SKITTER 2 robot

The Skitter 2 is a three legged transport vehicle designed to demonstrate the principle of a tripod walker in a multitude of environments. The tubular truss model of Skitter 2 is a proof of principal design. The model will replicate the operational capabilities of Skitter 2 including its ability to self-right itself. The project's focus was on the use of light weight tubular members in the final structural design. A strong design for the body was required as it will undergo the most intense loading. Triangular geometry was used extensively in the body, providing the required structural integrity and eliminating the need for cumbersome shear panels. Both the basic femur and tibia designs also relied on the strong geometry of the triangle. An intense literature search aided in the development of the most suitable weld techniques, joints, linkages, and materials required for a durable design. The hinge design features the use of spherical rod end bearings. In order to obtain a greater range of mobility in the tibia, a four-bar linkage was designed which attaches both to the femur and the tibia. All component designs, specifically the body, femur, and the tibia were optimized using the software package IDEAS 3.8A Supertab. The package provided essential deformation and stress analysis information on each component's design. The final structure incurred only a 0.0544 inch deflection in a maximum (worst case) loading situation. The highest stress experienced by any AL6061-T6 tubular member was 1920 psi. The structural integrity of the final design facilitated the use of Aluminum 6061-T6 tubing. The tubular truss structure of Skitter 2 is an effective and highly durable design. All facets of the design are structurally sound and cost effective

The Effect of Dual Task on Attentional Performance in Children With ADHD

Attention-deficit/hyperactivity disorder (ADHD) is a common psychiatric disorder without validated objective markers. Oculomotor behavior and executive motor control could potentially be used to investigate attention disorders. The aim of this study was to explore an oculomotor and postural dual task in children with ADHD. Forty-two children were included in the study, gathering children with ADHD (n = 21) (mean 8.15 age ± years 0.36) and sex-, age-, and IQ-matched typically developing children (TD). Children performed two distinct fixation tasks in three different postural conditions. Eye movements and postural body sway were recorded simultaneously, using an eye tracker and a force platform. Results showed that children with ADHD had poor fixation capability and poor postural stability when compared to TD children. Both groups showed less postural control on the unstable platform and displayed more saccades during the fixation task. Surprisingly, in the dual unstable platform/fixation with distractor task, the instability of children with ADHD was similar to that observed in TD children. “Top-down” dys-regulation mediated by frontal-striatal dysfunction could be at the origin of both poor inhibitory oculomotor deficits and impaired body stability reported in children with ADHD. Finally, we could assume that the fact both groups of children focused their attention on a secondary task led to poor postural control. In the future it could be interesting to explore further this issue by developing new dual tasks in a more ecological situation in order to gain more insight on attentional processes in children with ADHD.HIGHLIGHTS– Children with ADHD showed poor fixation capability when compared to TD children.– “Top-down” dys-regulation mediated by frontal-striatal dysfunction could be at the origin of both poor inhibitory oculomotor deficits and impaired body stability reported in children with ADHD.– Both groups of children focused their attention on the visual fixation task leading to poor postural control.– In the future it could be interesting to develop new dual tasks in an ecological situation in order to gain more insight on attentional processes in children with ADHD

Rapid tracking of extrinsic projector parameters in fringe projection using machine learning

In this work, we propose to enable the angular re-orientation of a projector within a fringe projection system in real-time without the need for re-calibrating the system. The estimation of the extrinsic orientation parameters of the projector is performed using a convolutional neural network and images acquired from the camera in the setup. The convolutional neural network was trained to classify the azimuth and elevation angles of the projector approximated by a point source through shadow images of the measured object. The images used to train the neural network were generated through the use of CAD rendering, by simulating the illumination of the object model from different directions and then rendering an image of its shadow. The accuracy to which the azimuth and elevation angles are estimated is within 1 classification bin, where 1 bin is designated as a ±10° patch of the illumination dome. To evaluate use of the proposed system in fringe projection, a pyramidal additively manufactured object was measured. The point clouds generated using the proposed method were compared to those obtained by an established fringe projection calibration method. The maximum dimensional error in the point cloud generated when using the convolutional network as compared to the established calibration method for the object measured was found to be 1.05 mm on average

Direct Imaging in Reflected Light: Characterization of Older, Temperate Exoplanets With 30-m Telescopes

Direct detection, also known as direct imaging, is a method for discovering and characterizing the atmospheres of planets at intermediate and wide separations. It is the only means of obtaining spectra of non-transiting exoplanets. Characterizing the atmospheres of planets in the <5 AU regime, where RV surveys have revealed an abundance of other worlds, requires a 30-m-class aperture in combination with an advanced adaptive optics system, coronagraph, and suite of spectrometers and imagers - this concept underlies planned instruments for both TMT (the Planetary Systems Imager, or PSI) and the GMT (GMagAO-X). These instruments could provide astrometry, photometry, and spectroscopy of an unprecedented sample of rocky planets, ice giants, and gas giants. For the first time habitable zone exoplanets will become accessible to direct imaging, and these instruments have the potential to detect and characterize the innermost regions of nearby M-dwarf planetary systems in reflected light. High-resolution spectroscopy will not only illuminate the physics and chemistry of exo-atmospheres, but may also probe rocky, temperate worlds for signs of life in the form of atmospheric biomarkers (combinations of water, oxygen and other molecular species). By completing the census of non-transiting worlds at a range of separations from their host stars, these instruments will provide the final pieces to the puzzle of planetary demographics. This whitepaper explores the science goals of direct imaging on 30-m telescopes and the technology development needed to achieve them.Comment: (March 2018) Submitted to the Exoplanet Science Strategy committee of the NA

Clinical and Experimental Factors Influencing the Efficacy of Neurofeedback in ADHD: A Meta-Analysis

Meta-analyses have been extensively used to evaluate the efficacy of neurofeedback (NFB) treatment for Attention Deficit/Hyperactivity Disorder (ADHD) in children and adolescents. However, each meta-analysis published in the past decade has contradicted the methods and results from the previous one, thus making it difficult to determine a consensus of opinion on the effectiveness of NFB. This works brings continuity to the field by extending and discussing the last and much controversial meta-analysis by Cortese et al. (1). The extension comprises an update of that work including the latest control trials, which have since been published and, most importantly, offers a novel methodology. Specifically, NFB literature is characterized by a high technical and methodological heterogeneity, which partly explains the current lack of consensus on the efficacy of NFB. This work takes advantage of this by performing a Systematic Analysis of Biases (SAOB) in studies included in the previous meta-analysis. Our extended meta-analysis (k = 16 studies) confirmed the previously obtained results of effect sizes in favor of NFB efficacy as being significant when clinical scales of ADHD are rated by parents (non-blind, p-value = 0.0014), but not when they are rated by teachers (probably blind, p-value = 0.27). The effect size is significant according to both raters for the subset of studies meeting the definition of “standard NFB protocols” (parents' p-value = 0.0054; teachers' p-value = 0.043, k = 4). Following this, the SAOB performed on k = 33 trials identified three main factors that have an impact on NFB efficacy: first, a more intensive treatment, but not treatment duration, is associated with higher efficacy; second, teachers report a lower improvement compared to parents; third, using high-quality EEG equipment improves the effectiveness of the NFB treatment. The identification of biases relating to an appropriate technical implementation of NFB certainly supports the efficacy of NFB as an intervention. The data presented also suggest that the probably blind assessment of teachers may not be considered a good proxy for blind assessments, therefore stressing the need for studies with placebo-controlled intervention as well as carefully reported neuromarker changes in relation to clinical response

Morning Plasma Melatonin Differences in Autism: Beyond the Impact of Pineal Gland Volume

While low plasma melatonin, a neuro-hormone synthesized in the pineal gland, has been frequently associated with autism, our understanding of the mechanisms behind it have remained unclear. In this exploratory study, we hypothesized that low melatonin levels in ASD could be linked to a decrease of the pineal gland volume (PGV). PGV estimates with magnetic resonance imaging (MRI) with a voxel-based volumetric measurement method and early morning plasma melatonin levels were evaluated for 215 participants, including 78 individuals with ASD, 90 unaffected relatives, and 47 controls. We first found that both early morning melatonin level and PGV were lower in patients compared to controls. We secondly built a linear model and observed that plasma melatonin was correlated to the group of the participant, but also to the PGV. To further understand the relationship between PGV and melatonin, we generated a normative model of the PGV relationship with melatonin level based on control participant data. We found an effect of PGV on normalized melatonin levels in ASD. Melatonin deficit appeared however more related to the group of the subject. Thus, melatonin variations in ASD could be mainly driven by melatonin pathway dysregulation

Evidence for a fast evolution of the UV luminosity function beyond redshift 6 from a deep HAWK-I survey of the GOODS-S field

We perform a deep search for galaxies in the redshift range 6.5<z<7.5, to measure the evolution of the number density of luminous galaxies in this redshift range and derive useful constraints on the evolution of their Luminosity Function. We present here the first results of an ESO Large Program, that exploits the unique combination of area and sensitivity provided in the near-IR by the camera Hawk-I at the VLT. We have obtained two Hawk-I pointings on the GOODS South field for a total of 32 observing hours, covering ~90 arcmin2. The images reach Y=26.7 mags for the two fields. We have used public ACS images in the z band to select z-dropout galaxies with the colour criteria Z-Y>1, Y-J<1.5 and Y-K<2. The other public data in the UBVRIJHK bands are used to reject possible low redshift interlopers. The output has been compared with extensive Monte Carlo simulations to quantify the observational effects of our selection criteria as well as the effects of photometric errors. We detect 7 high quality candidates in the magnitude range Y=25.5-26.7. This interval samples the critical range for M* at z>6 (M_1500 ~- 19.5 to -21.5). After accounting for the expected incompleteness, we rule out at a 99% confidence level a Luminosity Function constant from z=6 to z=7, even including the effects of cosmic variance. For galaxies brighter than M_1500=-19.0 we derive a luminosity density rho_UV=1.5^{+2.0}_{-0.9} 10^25 erg/s/Hz/Mpc3, implying a decrease by a factor 3.5 from z=6 to z~6.8. On the basis of our findings, we make predictions for the surface densities expected in future surveys surveys, based on ULTRA-VISTA, HST-WFC3 or JWST-NIRCam, evaluating the best observational strategy to maximise their impact.Comment: Accepted for publication in Astronomy & Astrophysic